Abstract: “In this paper we present a new method for detecting and classifying moving objects into humans and vehicles from a video surveillance scene. In this approach, the moving objects are firstly detected from the background using a background subtraction technique. Background subtraction algorithms are implemented in a MATLAB environment. A comparison for all the algorithms was made to determine which background subtractionalgorithm performs better with the proposed classifying algorithm. The algorithms were then tested using more than a video and many frames of the video was tested. Secondly, edge detection of moving objects was performed using Canny or Prewitt operations, while bounding boxes were implemented over the moving objects. Edge detection and bounding boxes were used before the classification step to simplify the classification.Finally, classifying the moving object into humans and vehicles was accomplished by finding the height-width ratio of the bounding box around the moving”

Keywords: background subtraction, classification, moving object detection.